Data models can represent relationships between information and can be used to analyze complex systems. For example, weather data models can represent weather patterns and can be used to determine likely future weather that will be experienced in various geographic areas. For instance, a weather data model can map detected weather information (e.g., current temperature, precipitation, pressure, dew point, wind speed, wind direction) at particular geographic locations to expected future weather that will be experienced at the same or different geographic locations. Such weather data models can be generated based on observed weather conditions over time at various geographic locations and using, for example, domain knowledge (expertise) about relationships between weather conditions in various geographic locations.
Distributed computing environments, such as cloud computer systems, allow for operations to be performed across multiple computers working in parallel. Each computational unit in a distributed environment, which may or may not be based on physical computational units (e.g., processors, computers, servers), can be managed by a centralized process and can operate independently of the other computing units. For example, a cloud computer system can distribute the processing of multiple different data sets across multiple computational units of the cloud computer system, which can each process their corresponding data set in parallel without interacting with the other computational units.